Literature DB >> 28735616

Research Techniques Made Simple: An Introduction to Use and Analysis of Big Data in Dermatology.

Mackenzie R Wehner1, Katherine A Levandoski2, Martin Kulldorff3, Maryam M Asgari4.   

Abstract

Big data is a term used for any collection of datasets whose size and complexity exceeds the capabilities of traditional data processing applications. Big data repositories, including those for molecular, clinical, and epidemiology data, offer unprecedented research opportunities to help guide scientific advancement. Advantages of big data can include ease and low cost of collection, ability to approach prospectively and retrospectively, utility for hypothesis generation in addition to hypothesis testing, and the promise of precision medicine. Limitations include cost and difficulty of storing and processing data; need for advanced techniques for formatting and analysis; and concerns about accuracy, reliability, and security. We discuss sources of big data and tools for its analysis to help inform the treatment and management of dermatologic diseases.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28735616      PMCID: PMC5600502          DOI: 10.1016/j.jid.2017.04.019

Source DB:  PubMed          Journal:  J Invest Dermatol        ISSN: 0022-202X            Impact factor:   8.551


  11 in total

Review 1.  Big Data, Big Opportunities, and Big Challenges.

Authors:  Jeffrey A Frelinger
Journal:  J Investig Dermatol Symp Proc       Date:  2015-11

2.  Geographic Clusters of Basal Cell Carcinoma in a Northern California Health Plan Population.

Authors:  G Thomas Ray; Martin Kulldorff; Maryam M Asgari
Journal:  JAMA Dermatol       Date:  2016-11-01       Impact factor: 10.282

3.  Association between cutaneous melanoma incidence rates among white US residents and county-level estimates of solar ultraviolet exposure.

Authors:  Thomas B Richards; Christopher J Johnson; Zaria Tatalovich; Myles Cockburn; Melody J Eide; Kevin A Henry; Sue-Min Lai; Sai S Cherala; Youjie Huang; Umed A Ajani
Journal:  J Am Acad Dermatol       Date:  2011-11       Impact factor: 11.527

4.  Drug safety data mining with a tree-based scan statistic.

Authors:  Martin Kulldorff; Inna Dashevsky; Taliser R Avery; Arnold K Chan; Robert L Davis; David Graham; Richard Platt; Susan E Andrade; Denise Boudreau; Margaret J Gunter; Lisa J Herrinton; Pamala A Pawloski; Marsha A Raebel; Douglas Roblin; Jeffrey S Brown
Journal:  Pharmacoepidemiol Drug Saf       Date:  2013-03-20       Impact factor: 2.890

5.  Histologic features of melanoma associated with CDKN2A genotype.

Authors:  Michael R Sargen; Peter A Kanetsky; Julia Newton-Bishop; Nicholas K Hayward; Graham J Mann; Nelleke A Gruis; Margaret A Tucker; Alisa M Goldstein; Giovanna Bianchi-Scarra; Susana Puig; David E Elder
Journal:  J Am Acad Dermatol       Date:  2015-01-13       Impact factor: 11.527

6.  Dermatologist-level classification of skin cancer with deep neural networks.

Authors:  Andre Esteva; Brett Kuprel; Roberto A Novoa; Justin Ko; Susan M Swetter; Helen M Blau; Sebastian Thrun
Journal:  Nature       Date:  2017-01-25       Impact factor: 49.962

7.  Measures of clinical severity, quality of life, and psychological distress in patients with psoriasis: a cluster analysis.

Authors:  Francesca Sampogna; Francesco Sera; Damiano Abeni
Journal:  J Invest Dermatol       Date:  2004-03       Impact factor: 8.551

8.  Identification of Susceptibility Loci for Cutaneous Squamous Cell Carcinoma.

Authors:  Maryam M Asgari; Wei Wang; Nilah M Ioannidis; Jacqueline Itnyre; Thomas Hoffmann; Eric Jorgenson; Alice S Whittemore
Journal:  J Invest Dermatol       Date:  2016-01-29       Impact factor: 8.551

9.  Validation of claims data algorithms to identify nonmelanoma skin cancer.

Authors:  Melody J Eide; J Mark Tuthill; Richard J Krajenta; Gordon R Jacobsen; Marc Levine; Christine C Johnson
Journal:  J Invest Dermatol       Date:  2012-04-05       Impact factor: 8.551

10.  The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.

Authors:  Ronald Margolis; Leslie Derr; Michelle Dunn; Michael Huerta; Jennie Larkin; Jerry Sheehan; Mark Guyer; Eric D Green
Journal:  J Am Med Inform Assoc       Date:  2014-07-09       Impact factor: 4.497

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  3 in total

1.  Meeting the challenge: Health information technology's essential role in achieving precision medicine.

Authors:  Teresa Zayas-Cabán; Kevin J Chaney; Courtney C Rogers; Joshua C Denny; P Jon White
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

Review 2.  Machine Learning in Dermatology: Current Applications, Opportunities, and Limitations.

Authors:  Stephanie Chan; Vidhatha Reddy; Bridget Myers; Quinn Thibodeaux; Nicholas Brownstone; Wilson Liao
Journal:  Dermatol Ther (Heidelb)       Date:  2020-04-06

Review 3.  Influential Usage of Big Data and Artificial Intelligence in Healthcare.

Authors:  Yan Cheng Yang; Saad Ul Islam; Asra Noor; Sadia Khan; Waseem Afsar; Shah Nazir
Journal:  Comput Math Methods Med       Date:  2021-09-06       Impact factor: 2.238

  3 in total

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